The mysteries of life and the cosmos are too complex, even for science; so humility please in all endeavors

Back in 2008, Stuart Kauffman, the world-renown complexity scientist and biologist, published a very interesting book, Reinventing the Sacred: A New View of Science, Reason and Religion.  Most have probably heard about it or even read it.  I am not religious or belong to any faith tradition, but I found it very interesting science.

For me, what makes it an interesting read is that it is classic Kauffman.

What Makes Stuart Kauffman So Brilliant

For me, Kauffman is a brilliant (and highly unique) scientist and scholar because he is always able to take the next step, intellectually, into ideas that seem, at first, incredibly odd or strange or just downright impossible.  A little later, however, as the rest of us come along, and as time goes by, we come to realize that, you know what, minor issues aside, he has a pretty good idea---with "good idea" meaning that it has proven scientifically useful. Perhaps the best example of this point is Kauffman's ground-breaking notion that self-organization is the other half of the evolutionary coin.  The other example---and the focus of my current post---is his book, Inventing the Sacred.

Reinventing the Sacred

Here (from its back cover) is a quick summary of the book's central theme:
"Consider the complexity of a living cell after 3.8 billion years of evolution. Is it more awesome to suppose that a transcendent God fashioned the cell at a stroke, or to realize that it evolved with no Almighty Hand, but arose on its own in the changing biosphere?  In this bold and fresh look at science and religion, complexity theorist Stuart Kauffman argues that the qualities of divinity that we revere—creativity, meaning, purposeful action—are properties of the universe that can be investigated methodically. He offers stunning evidence for this idea in an abundance of fields, from cell biology to the philosophy of mind, and uses it to find common ground between belief systems often at odds with one another. A daring and ambitious argument for a new understanding of natural divinity, Reinventing the Sacred challenges readers both scientifically and philosophically."

So, What is My Point?

Sorry for the delay in making my point, but the setup was necessary.  Whether you agree with Kauffman or not, I think he is making a more general point.  Or, at least, that is my read.  As a backdrop argument, I think he is saying that arrogance in science or religion will get us nowhere; and fighting amongst ourselves over the power to be "right at the expense of all other views," be it in religion, science or anything in-between, is destructive.  As Foucault said, polemics (in contrast to debate) are useless.

Case in point.  Over the past few months I have come across the following post (A review of Reinventing the Sacred) on at least a dozen or more occasion.  Best I can surmise, it was originally written by the British paleontologist, evolutionary biologist (and let us also not forget, Tolkienist), Henry Gee

While critical of Kauffman, Gee's point is my own--or maybe, my point is Gee's; that's probably better stated.  Actually, my point is Gee's point, which I also think is, as a backdrop, Kauffman's point.  It is a variation on what I just said above: C'mon folks, all those certain of their science or religion; drop the arrogance and show a bit more humility, please!  Kauffman may or may not be right.  So, let's debate the validity of his ideas, but drop the polemics.  Otherwise, you won't get invited to all the cool parties, as your such a 'debbie downer' conversation hog.

Here is Gee's post in its entirety:

An argument that complex systems transcend natural law, and thus are symbolically sacred.

Reinventing the Sacred
A New View of Science, Reason and Religion

By Stuart A. Kauffman

In Unweaving the Rainbow, Richard Dawkins boasted that he once told a child that Santa Claus didn't exist. The argument was that Santa couldn't possibly visit all the world's deserving homes in a single night, quite apart from the physical difficulties of flying reindeer, narrow chimney stacks, and so on.

As well as illustrating the intellectual level of Dawkinsian discourse, this anecdote betrays a lack of knowledge of contemporary physics. Santa could do what he does quite handily, you see, if you consider him as a macroscopic quantum object - something that behaves according to the weird world of quantum physics but is large enough to be visible.

In such a guise, Santa could appear in as many places as he wanted to, simultaneously, without having to negotiate chimneys, provided nobody was watching. If he were caught in the act, his wavefunction - the probability that he might be everywhere at once - would collapse and he'd be revealed as your grandpa, after all.

And quantum effects are manifested at the macro scale only in extremely cold conditions, which explains why one routinely addresses one's Christmas list to Lapland or the North Pole, rather than, say, Brazil or Equatorial Guinea.

My Quantum Santa Hypothesis (QSH) works better than Dawkins' classical one because it explains the taboo about watching Santa at work, as well as his traditional location in cold climates - aspects Dawkins fails to tackle. The QSH explains more of the evidence in a single theoretical scheme than his does.

This is not to say that Santa exists, however. I have never challenged Professor Dawkins with the QSH. But the reaction of some of his acolytes to my original exposition (in the Guardian of Dec. 14, 2000) was predictable: Anyone who challenged Dawkins' view on this question was obviously a believer, and therefore not to be trusted.

This simplistic, with-us-or-against-us worldview is as deficient in subtlety as it is in humor. We know what we know because of science, it says. Science explains everything. So anything that falls outside that explanatory system must be false, illusory, even evil. What such defenders of science fail to see is that this line of reasoning betrays a dreadful misuse of the scientific method.

Theoretical biologist Stuart A. Kauffman, who taught at the University of Pennsylvania from 1975 to 1995, is unlikely to fall into that trap. In Reinventing the Sacred, he takes aim at reductionist reasoning, much used in the sciences. Reductionist thinking takes complicated systems to pieces, studies all the pieces in isolation, and then sticks them back together again. Powerful and useful. Kauffman argues, however, that reductionism fails to explain the properties of systems that are "emergent" - that come into being by virtue of their inherent complexity, and whose properties cannot be explained by reducing them to the simpler systems from which they arise.

Say you have a few pounds of carbon compounds and a bucket of water, and you know how these behave chemically. It's nevertheless impossible to predict that the combination of these substances might be capable of evolving into structures (human beings) capable of self-reflection: Cogito ergo sum. Darwinian adaptations, agency, awareness, economics and human history are all emergent, and cannot be reduced to what Kauffman calls the physicists' system of "particles in motion."

Caution: This is not the same thing as the "irreducible complexity" that the intelligent-design camp claims is a sign of the hand of God. Such is no more than politically motivated special pleading. Instead, Kauffman goes to great lengths to suggest, in intense detail and with a rigor that, frankly, takes no prisoners, how emergence arises.

The message in chapter after chapter is that any reasonably complex system - whether the global biosphere or human technological ingenuity - betrays a "ceaseless creativity" that transcends fundamental natural laws and requires no prime mover.

Kauffman's reasoning is, in the main, faultless. It falls down, however, in two places. The first is his proposal that consciousness is based on the quantum mechanical properties of cellular substructures. Some recent work does show that certain proteins, in the dense milieu of cells, can manipulate electrons Santa-fashion, keeping all quantum possibilities open for as long as possible.

This idea is fascinating, but Kauffman appears to speak as if such properties were confined to neurons in the brain. Nowhere does he explain why they should not exist in other kinds of cell - a flaw that exposes him to accusations of arguing that brain cells are somehow exceptional. By the same token, he dismisses, out of hand, the idea that "mind" might be an emergent property of the trillion-fold interconnectedness of billions of neurons - a casual swipe that goes against everything else he says in the book about complex systems.

The second failure is the whole God business. The concluding chapters are more readable than the rest (in a book that is often an eye-watering challenge to read), but they degenerate into a repetitive mantra in which Kauffman says that the "ceaseless complexity" of the world, while not being evidence for a Creator God, should somehow be "symbolic" of God, or, at least, of something "sacred." He cannot prove this logically, he says; he can only try to persuade us.

This appeal to a kind of primitive pantheism is both sincere and charming, but in the end it is simply more special pleading. The fact is that in Kauffman's scheme, God is unnecessary, even if reductionism fails, so in the end one wonders about the point of preserving a sense of God.

To be sure, certain scientists could surely use a dose of humility before the evidence. Science cannot explain why human beings act and feel and think in the way they do in specific circumstances, and spirituality might even be important, valuable and worthy of respect. But what does God have to do with any of this?

I'm hedging my bets - I'm asking Santa for a quantum computer for Christmas.

Henry Gee is a senior editor of the science magazine Nature. 


New Version of Complexity Map---The Complexity Map Version 5

Hello everyone!  As you can see above,  I have (once again) updated my map of the complexity sciences.



To cite this map use the following

Castellani, Brian 2013. Complexity Map Version 5.  Sociology and Complexity Science Blog. http://sacswebsite.blogspot.com/2013/07/the-complexity-map-version-5.html.

Complexity Map Version 5

Complexity Map Version 5 is a massive update, based on my continuing attempt to keep the map as useful as possible to an ever-growing field and audience.  For Version 5, I went back to the beginning, as they say, trying to "fill in" the map and its major trajectories by:
  1. Breaking larger areas of study (such as social complexity or the dynamics of complex systems) into sets of smaller but interconnected areas of research.
  2. Adding newer or smaller areas of study that have stabilized into identifiable fields of scholarship, such as computational biology, visual complexity or data science.
  3. Adding more scholars (both major and minor) to reflect the widening depth of the field.  

Reading Complexity Map Version 5

This map is a macroscopic, trans-disciplinary introduction to the complexity sciences.  Moving from left to right, it is read in a roughly historical fashion, evolving along the field’s five major intellectual traditions: dynamical systems theory (purple), systems science (light blue), complex systems theory (yellow), cybernetics (grey) and artificial intelligence (orange).  Placed along these traditions are many of the key scholarly themes in the complexity sciences.  A theme’s color identifies the historical tradition with which it is best associated, even if a theme is placed on a different intellectual trajectory.  Themes in brown denote discipline-specific topics, which help illustrate how the complexity sciences are applied to different content. Double-lined themes denote the intersection of a tradition with an entirely new field of study, as in the case, for example, of visual complexity or agent-based modeling.  Connected to themes are the scholars who founded or exemplify work in that area. 

Mapping Science: A Few Lessons Learned

I learned a few lessons about the challenges of mapping the history of science.

First, as Foucault says, there are only histories of the present.  History is largely a backward looking profession, charting the movements of things across time and place from the present position of the historian.  For example, I remember my father-in-law, Len Rusnak, saying that the further away we get from certain presidents in the states, for example, such as Truman, the better or worse they start looking, depending upon the lines of influence we are drawing from them to the present.  The same seems to be true of science.

I have noticed over the years that, as new area of study emerge within the complexity sciences, new historical lines of influence are established, new scholars emerge as more or less important, and new historical lineages are developed.  Case in point.  If you go back to the reviews of complexity written in the late 1990s, the emphasis was, historically speaking, almost entirely on systems science, cybernetics and the work taking place at the Santa Fe Institute, in New Mexico, USA.  More recently, however, lots of smaller and more specific histories have emerged.  In the social sciences, for example, ties are being made to all sorts of epistemological positions, from postmodernism to poststructuralism to constructionism to critical realism.  And, while a scholar like Per Bak and his work on self-organized criticality, for example, was a "massively major" field of study back in the 1990s, he and his work have receded into the background, as new areas and scholars have come into the picture, so to speak, and have taken over.  As a result, the old stories have receded or softened a bit, turning into a more complex and nuanced storyline.  In response, I have found myself having to constantly evolve, develop and adapt the complexity map. 

Second, it seems that, given how wide-reaching the field is now, everyone has their own personal standpoint on the history of complexity.  I am constantly told, for example, that the complexity map, "while useful, is incomplete!" or that, "while it gets at most of the major stuff, it is a partial view of just one person!"  What?  Of course it is!  Have you not read anything on the philosophy or epistemology of complexity, going all the way to the early scholars developing the field of cybernetics and systems science?  The big, big point made by all these scholars is that all maps, models and theories of complexity and its interdisciplinary study will be, by definition, incomplete!  I mean, we are talking about an approach to science that, as Stephen Hawking and others have suggested, will most likely become, in the next fifty years, the dominant definition of science, with the word "complexity" simply being dropped.  So, C'mon folks!"

Given such realities, what is the goal of the current map?  While it strives to be reasonably exhaustive and impartial, it ultimately strives to help people into the field, to give them a broad understanding of many of its key fields of study and important scholars, pointing them in a variety of directions which they can explore further, drilling down, as they say, into finer and finer levels of analysis.  Or better yet, giving them the tools to develop their own maps, their own networks of connections and so forth.  It would be interesting, for example, to give people only the names and areas of study on this map and see how they arrange them.  I am sure that, while common patterns of arrangement would emerge, major differences would exist, never to be resolved.

Third, it is clear that, far from slowing down, the complexity sciences are advancing at an incredible speed, as this field's various approaches to modeling the topics of science are taken up across the academy!  It is very exciting to watch and map this progress, as the work scholars are doing is just incredible!

So, let's think of this map as an evolving dialogue (with the appropriate paper-trail) if you will: a debate, an argument, or (better yet) a charted negotiated ordering that has emerged through our complex interactions with the larger scientific history of which we are a part.  As such, I am sure that Version 10 of the map, to my own detriment (Ha!), is not too far off in the immediate future.  phew!








social science departments need to innovate the teaching of method by embracing new approaches to big data, statistics, computational modeling and complexity

The title of this post says it all: social science departments need to innovate the teaching of method by embracing new approaches to big data, computational modeling and complexity.

As I discussed in a previous post---CLICK HERE---the UK is currently implementing a major, new academic initiative to address, at the undergraduate level, the underdeveloped methodological skills of students majoring in the social sciences, particularly in the areas of quantitative method and statistics. The initiative is called, appropriately enough, the Quantitative Methods (QM) Programme.

In response, a variety of UK scholars from different disciplines and areas of study are innovating the teaching of method.  One major area of advancement, which I address on my map of complexity, is data visualization--a whole new field of study that intersects data mining, art, design, web science, computational science and so forth.

For example, I am on a UK listserv for teaching method and came across the following SEMINAR that was held on teaching data visualization.  Here is how they describe the even on the website for the seminar, which includes two of the keynote presentations:


The Department of Social Sciences at Loughborough University is currently undertaking a pedagogical research project, sponsored by the ESRC, which involves introducing a new 22 week quantitative data analysis module for first year criminology and sociology students. The module emphases visual learning and teaching strategies and resources. It also assesses students using a portfolio of achievement rather than relying solely on the more traditional ‘statistical report’ format. The new module will be delivered for the first time in the academic year 2013-14 at undergraduate level 1.The objectives of the HEA sponsored workshop are to discuss the progress of this project as well as to explore more generally the types of visual learning and teaching strategies used to teach research methods and quantitative data analysis across Social Science departments in the HE sector.

Time to Play Catch Up

Social Scientists in the states and elsewhere need to "get on-board" as they say, with these types of advances taking place in the UK and elsewhere.  And (this is key) not just at the elite institutes.  These sorts of innovations need to be taking place at "anywhere and everywhere" colleges and universities and community colleges and technology schools.  We live in a world, now, where virtual and physical reality are almost entirely blurred.  Mean, median and mode and a few bar graph charts don't "cut it" anymore as effective techniques for measuring and presenting this reality.  C'mon folks, there are lots of exciting things happening and we need to share them with our students!!!!!!!

Here is a list of a few examples to explore on the topic of data visualization and data science:

Places and Spaces: Mapping Science project, run by Katy Börner and Todd Theriault.

A good introductory article summarizing the field

A Wikipedia article introducing the field of data visualization

A Wikipedia article introducing data science and big data

A website by one of the top people in the field, on visual complexity

A great interactive map, found at TIME Magazine, of the USA and population sizes by cities.

A good review of two recently published books on visual complexity


The Complexities of Space and Place

I remember, back in the days of postmodernism, a colleague, a geographer, was giving a talk on postmodernism and geography.  A few of my colleagues commented, saying something like, "What does geography have to do with pomo?"  Turns out, the answer was a lot: narratives, national identity, notions of the globe and global, the epistemology of space and place.... It just keeps going.

A few years back I went to see the same colleague, my geographer friend, lecture on complexity and geography.  Same response from colleagues, albeit even more ignorant: what is all that complexity stuff and what does it have to do with geography?  Turns out, the answer is, again, a lot: residential mobility and Schelling segregation, networks and the dynamics of space and place within them, global network society, Big Data and geospatial analysis, smart phones and Google maps, mapping disease spread, social mobilities, the blurring of spatial boundaries, the geography of the internet....  Again, it just keeps going.

In fact, in my mind, one of the most exciting new area of analysis in the complexity sciences today is the complexities of space and place.  One of my students, in fact, who just graduated with his bachelors, is heading on to study complexity and geospatial analysis, and he majored in sociology, with an emphasis on health and health care.

In his mind, and in mine, this is "where it is at in medical sociology," in many ways--from the sociology of population and community health to epidemiology and the geography of health and wellbeing to the built environment and urban planning to health behaviors and networks.  And, don't forget all the methods, from agent-based models to networks to GIS software.

There are so many people to mention and lots of websites and new centers and areas of research to highlight.  Impossible for a quick blog.

Here, however, are a few to get you going:

Michael Batty and the complexities of cities

Centre for Advanced Spatial Analysis

Nigel Thrift and the geography of complexity

David O'Sullivan and geography and complexity science

Barabasi and colleagues on mobility in networks

John Urry and social mobilities

Manuel Castells and global network society

Complexities of place and health

lots and lots of stuff.  very exciting work.